| |
| import numpy as np |
| import networkx as nx |
| import pandas as pd |
| maxscore = 19 |
| ref_score_list = {'Affinity Capture-MS':17, |
| 'Affinity Capture-Western':14, |
| 'Two-hybrid':1, |
| 'Reconstituted Complex':2, |
| 'Proximity Label-MS':7, |
| 'Co-fractionation':5, |
| 'Biochemical Activity':11, |
| 'Affinity Capture-RNA':13, |
| 'Co-localization':4, |
| 'Co-purification':6, |
| 'PCA':9, |
| 'Co-crystal Structure':18, |
| 'FRET':10, |
| 'Protein-peptide':16, |
| 'Affinity Capture-Luminescence':12, |
| 'Far Western':8, |
| 'Protein-RNA':3} |
|
|
| def read_biogrid(f, mapping): |
| edges = [] |
| data = pd.read_csv(f, sep="\t") |
| source_ = data['Entrez Gene Interactor A'].values |
| target_ = data['Entrez Gene Interactor B'].values |
| ref = data['Experimental System'].values |
| score_ = np.array([ref_score_list[i] for i in ref]) |
| for i in range(len(source_)): |
| source = str(source_[i]) |
| target = str(target_[i]) |
| score = score_[i] |
| if source in mapping and target in mapping: |
| source = mapping[source] |
| target = mapping[target] |
| temp = tuple(sorted((source, target))) |
| |
| |
| temp = temp + (score,) |
| edges.append(temp) |
| G = nx.Graph() |
| G.add_weighted_edges_from(edges) |
| print("BioGRID") |
| |
| for n in G.nodes: |
| if "," in n: print(n) |
| return G |
|
|
|
|
| def read_menche(f, mapping): |
| edges = [] |
| with open(f) as fin: |
| for line in fin: |
| if line.startswith("#"): continue |
| source = line.split()[0] |
| target = line.split()[1] |
| if source in mapping and target in mapping: |
| source = mapping[source] |
| target = mapping[target] |
| temp = tuple(sorted((source, target))) |
| temp = temp + (maxscore,) |
| edges.append(temp) |
| G = nx.Graph() |
| G.add_weighted_edges_from(edges) |
| print("Menche et al. 2015") |
| |
| for n in G.nodes: |
| if "," in n: print(n) |
| return G |
|
|
|
|
| def read_huri(f, mapping): |
| edges = pd.read_csv(f, sep="\t", header=None) |
| edges['weight'] = maxscore |
| edges.columns = ["source", "target", "weight"] |
| G = nx.from_pandas_edgelist(edges, source='source', target='target', edge_attr='weight') |
| G = nx.relabel_nodes(G, mapping) |
| for n in G.nodes: |
| if "," in n: print(n) |
| nodes_to_remove = [] |
| for n in G.nodes: |
| if n.startswith("ENS"): nodes_to_remove.append(n) |
| G.remove_nodes_from(nodes_to_remove) |
|
|
| print("HuRI") |
| |
| return G |
|
|
|
|
| def read_mapping(f): |
| entrez2hgnc = dict() |
| ensembl2hgnc = dict() |
| with open(f) as fin: |
| for line in fin: |
| hgnc_id = line.split("\t")[1].strip() |
| entrez_id = line.split("\t")[2].strip() |
| ensembl_id = line.split("\t")[3].strip() |
| if hgnc_id != "" and entrez_id != "": |
| if entrez_id in entrez2hgnc: |
| print(entrez_id, hgnc_id, entrez2hgnc[entrez_id]) |
| if hgnc_id != entrez2hgnc[entrez_id]: hgnc_id = ",".join([entrez2hgnc[entrez_id], hgnc_id]) |
| entrez2hgnc[entrez_id] = hgnc_id |
| if hgnc_id != "" and ensembl_id != "": |
| if ensembl_id in ensembl2hgnc: |
| print(ensembl_id, hgnc_id, ensembl2hgnc[ensembl_id]) |
| if hgnc_id != ensembl2hgnc[ensembl_id]: hgnc_id = ",".join([ensembl2hgnc[ensembl_id], hgnc_id]) |
| ensembl2hgnc[ensembl_id] = hgnc_id |
| print("Num mapping entrez2hgnc", len(entrez2hgnc)) |
| print("Num mapping ensembl2hgnc", len(ensembl2hgnc)) |
| return entrez2hgnc, ensembl2hgnc |
|
|
|
|
| def union_G(biogrid_G, menche_G, huri_G, ppi_f): |
| ppi = nx.Graph() |
| ppi.add_edges_from(biogrid_G.edges(data=True)) |
| ppi.add_edges_from(menche_G.edges(data=True)) |
| ppi.add_edges_from(huri_G.edges(data=True)) |
| print("Overlap with PPI + BioGRID:", len(set(list(ppi.nodes)).intersection(set(list(biogrid_G.nodes))))) |
| print("Overlap with PPI + Menche:", len(set(list(ppi.nodes)).intersection(set(list(menche_G.nodes))))) |
| print("Overlap with PPI + HuRI:", len(set(list(ppi.nodes)).intersection(set(list(huri_G.nodes))))) |
| print("Overlap with BioGRID + Menche:", len(set(list(biogrid_G.nodes)).intersection(set(list(menche_G.nodes))))) |
| print("Overlap with BioGRID + HuRI:", len(set(list(biogrid_G.nodes)).intersection(set(list(huri_G.nodes))))) |
| print("Overlap with HuRI + Menche:", len(set(list(huri_G.nodes)).intersection(set(list(menche_G.nodes))))) |
| print("Overlap with BioGRID + HuRI + Menche:", len(set(list(biogrid_G.nodes)).intersection(set(list(huri_G.nodes)), set(list(menche_G.nodes))))) |
| print("Full PPI") |
| |
| nx.write_edgelist(ppi, ppi_f, data=True) |
| return ppi |
|
|
|
|
| def main(): |
| entrez2hgnc, ensembl2hgnc = read_mapping("../../data/ppi/2022-03-PPI/hgnc2map.txt") |
| biogrid_G = read_biogrid("../../data/ppi/2022-03-PPI/BIOGRID-MV-Physical-4.4.207.tab3.txt", entrez2hgnc) |
| menche_G = read_menche("../../data/ppi/2022-03-PPI/DataS1_interactome.tsv", entrez2hgnc) |
| huri_G = read_huri("../../data/ppi/2022-03-PPI/HuRI.tsv", ensembl2hgnc) |
| ppi = union_G(biogrid_G, menche_G, huri_G, "../../data/ppi/2022-03-PPI/ppi_edgelist.txt") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
|
|
